Cell formation in group technology using constraint programming and Boolean satisfiability

Cell formation consists in organizing a plant as a set of cells, each of them containing machines that process similar types or families of parts. The idea is to minimize the part flow among cells in order to reduce costs and increase productivity. The literature presents different approaches devoted to solve this problem, which are mainly based on mathematical programming and on evolutionary computing. Mathematical programming can guarantee a global optimal solution, however at a higher computational cost than an evolutionary algorithm, which can assure a good enough optimum in a fixed amount of time. In this paper, we model and solve this problem by using state-of-the-art constraint programming (CP) techniques and Boolean satisfiability (SAT) technology. We present different experimental results that demonstrate the efficiency of the proposed optimization models. Indeed, CP and SAT implementations are able to reach the global optima in all tested instances and in competitive runtime.     

An experimental study for the effect of different clearances on burr, smooth-sheared and blanking force on aluminium sheet metal

In this study, an experimental study was carried out to examine the effect of different clearances on smooth-sheared depth, burr height and blanking force. Aluminium sheet metals with 0.8, 1, and 1.5 mm thicknesses were used in the experiments. These experiments were carried out in circular blanking dies to 6, 8, 10, and 12 mm diameters. Six different clearances (0.009, 0.064, 0.12, 0.175, 0.231 and 0.287 mm) were used for every material and diameter. The results of the experiment show that burr, smooth-sheared and punch force is strongly related to the clearance value. The results are in agreement with the results of previous theoretical and experimental work in the literature.     

The Classical Theory of Invariants and Object Recognition Using Algebraic Curve and Surfaces

Combining implicit polynomials and algebraic invariants for representing and recognizing complicated objects proves to be a powerful technique. In this paper, we explore the findings of the classical theory of invariants for the calculation of algebraic invariants of implicit curves and surfaces, a theory largely disregarded in the computer vision community by a shadow of skepticism. Here, the symbolic method of the classical theory is described, and its results are extended and implemented as an algorithm for computing algebraic invariants of projective, affine, and Euclidean transformations. A list of some affine invariants of 4th degree implicit polynomials generated by the proposed algorithm is presented along with the corresponding symbolic representations, and their use in recognizing objects represented by implicit polynomials is illustrated through experiments. An affine invariant fitting algorithm is also proposed and the performance is studied.     

Episodic memory and metamemory in Parkinson’s disease patients.

This study investigated episodic memory and metamemory for verbs and nouns in patients who have cognitive impairments associated with Parkinson’s disease (PD). PD patients and healthy control participants were asked to recall word pairs and provide feeling-of-knowing (FOK) judgments for the items they were unable to recall. This was followed by a 4-alternative recognition test. PD patients were impaired in both recall and recognition, compared with controls. In terms of metamemory, PD patients were less confident in their ability to recognize the unrecalled items in a future recognition test. Most important, accuracy of PD patients’ FOK judgments was not above chance and was lower than that of control participants. The PD group correctly recognized fewer verbs than nouns, but type of material (verb vs. noun) had no impact on recall or FOK judgments. In addition, contribution of executive functions to FOK accuracy was different in PD patients and controls. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fuzzy rule base optimization of a compliant wrist sensor for robotic assembly

The problem of part mating and assembly with close tolerances has been addressed in the past by active or passive compliance and by force/position control. With ambient sensor and transmission noise and with imprecise measurements it is often difficult to attain high precision in manipulator positioning. A compliant wrist position sensor with a fuzzy logic rule base was designed by the author to address this problem. In this article, after a brief review of this sensor, optimization of its fuzzy rule base is discussed. The optimization results are then presented. © 1996 John Wiley & Sons, Inc.     

The hydro-abrasive erosion wear behavior of duplex-treated surfaces of AISI H13 tool steel

The influence of duplex surface treatments consisting of a DC-pulsed plasma nitriding process and subsequent coatings of CrN and TiAlN deposited by physical vapor deposition(PVD)on AISI H13 tool steel was studied in this article.The treated samples were characterized using metallographic techniques,SEM,EDS,and microhardness methods.Hydro-abrasive erosion wear tests were performed in a specifically designed wear tester in which the samples were rotated in a wear tank containing a mixture of distilled water and ceramic abrasive chips with a fixed rotational speed.The wear rates caused by the abrasive particle impacts were assessed based on accumulated weight loss measurements.The worn surfaces were also characterized using optical microscopy,SEM,and EDS.Microhardness measurements indicated a significant increase in the surface hardness of the duplex-treated samples.The surfaces of the samples with the TiAlN coating were approximately 15 times harder than that of the untreated samples and 3 times that of the plasma nitrided samples.Hydro-abrasive erosion wear results showed that the duplex surface treatments,especially the CrN coating,displayed the highest erosion wear resistance.     

Varnish layer hardness of oriental beech (fagus orientalist L.) wood as affected by impregnation and bleaching

The impacts of impregnation and bleaching on the varnish layer hardness of Oriental beech (Fagus orientalist L.) wood were investigated. A number of bleaching combinations {[NaOH−H₂O₂], [NaOH−Ca(OH)₂−H₂O₂], [NaOH−MgSO₄−H₂O₂] [NaHSO₃−H₂C₂O₄], [NaSiO₃−H₂O₂], [KMnO₄+NaHSO₃+H₂O₃]} were applied at 18% concentration for bleaching to both impregnated and unimpregnated specimens of Oriental beech wood. Subsequently, water-based (WB) varnish was coated over the samples and the varnish layer hardness values were determined in accordance with ASTM D 4366-95. All of the chemicals used for bleaching reduced the surface hardness. However, after varnish coating, the hardness of most samples was similar to that of the varnish-coated natural (control) samples.     

Determination of the quality and purity characteristics of olive oils obtained from different regions of Turkey,depending on climatic changes

Virgin olive oils (VOOs) obtained from olives grown in different regions of Turkey under changing climatic conditions sometimes show different sensory and chemical properties. This study was planned to determine whether these deviations are due to climatic changes or not. For this purpose, five different olive varieties (Ayvalık, Memecik, Gemlik, Nizip Yağlık, Kilis Yağlık) of commercial importance were harvested from the provinces/districts (four different region) where cultivation is intense during the 2017/2018–2020/2021 harvest years. Every year, olive samples were collected from 3 orchards from 13 provinces/districts. One hundred and fifty-six samples were subjected to the purity, quality and sensory analysis. Basic climatic values (average, minimum and maximum temperature, humidity and precipitation) were examined for four consecutive years. All of the examined olive oil samples were determined within the legal limits in terms of fatty acid composition and fatty acid ethyl ester values. However, delta-7-stigmastenol value from the sterol composition was found to be above 0.5% in some samples in all the years studied (total 21 samples). Delta-7-stigmastenol values of olive oil samples varied between 0.16% and 1.14%. Multiple linear regression analysis was applied using a genetic algorithm-based inverse least squares method to determine whether there is a relationship between climate data and delta-7-stigmastenol values. According to this result, it has been determined that the delta-7-stigmastenol value is high when the annual average relative humidity is low and the annual average temperature is high. There is an urgent need to make forward-looking plans due to climate change.     

Tensile Bond Strength of a Highly Cross-Linked Denture Tooth to the Compression-Molded and Injection-Molded Denture Base Polymers

This study compared tensile bond strengths between conventional compression-molded heat (HC)-, auto (AP)-, and microwave-polymerized (MC) poly(methyl methacrylate)-based denture resins and a relatively new injection-molded, microwave-polymerized polyurethane based resin (MI) bonded to a highly cross-linked denture tooth. In the first part of the experiments, denture teeth were used as received. In the second part, they were treated with dichloromethane to see its effect on bonding of conventional denture bases (HCS and APS). Bond strength was tested in tension according to ADA specification No.15. The results showed that the HC group failed cohesively because of higher interface bonding (49.95 MPa) compared with those of the others (AP: 25.41 MPa; MC: 22.06 MPa; MI: 20.02 MPa). The application of dichloromethane improved bond strengths of HCS and APS groups (60.61 and 32.03 MPa, respectively). It was suggested that dichloromethane could be applied on the denture teeth ridge lap area prior to denture base processing to enhance adhesion between the tooth/resin.